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1from __future__ import annotations
3from collections import defaultdict
4from collections.abc import Iterable
5from copy import copy
6from functools import lru_cache, partial
7from typing import TYPE_CHECKING, Any
9from pydantic_core import CoreSchema, PydanticCustomError, ValidationError, to_jsonable_python
10from pydantic_core import core_schema as cs
12from ._fields import PydanticMetadata
13from ._import_utils import import_cached_field_info
15if TYPE_CHECKING:
16 pass
18STRICT = {'strict'}
19FAIL_FAST = {'fail_fast'}
20LENGTH_CONSTRAINTS = {'min_length', 'max_length'}
21INEQUALITY = {'le', 'ge', 'lt', 'gt'}
22NUMERIC_CONSTRAINTS = {'multiple_of', *INEQUALITY}
23ALLOW_INF_NAN = {'allow_inf_nan'}
25STR_CONSTRAINTS = {
26 *LENGTH_CONSTRAINTS,
27 *STRICT,
28 'strip_whitespace',
29 'to_lower',
30 'to_upper',
31 'pattern',
32 'coerce_numbers_to_str',
33 'ascii_only',
34}
35BYTES_CONSTRAINTS = {*LENGTH_CONSTRAINTS, *STRICT}
37LIST_CONSTRAINTS = {*LENGTH_CONSTRAINTS, *STRICT, *FAIL_FAST}
38TUPLE_CONSTRAINTS = {*LENGTH_CONSTRAINTS, *STRICT, *FAIL_FAST}
39SET_CONSTRAINTS = {*LENGTH_CONSTRAINTS, *STRICT, *FAIL_FAST}
40DICT_CONSTRAINTS = {*LENGTH_CONSTRAINTS, *STRICT, *FAIL_FAST}
41GENERATOR_CONSTRAINTS = LENGTH_CONSTRAINTS
42SEQUENCE_CONSTRAINTS = {*LENGTH_CONSTRAINTS, *FAIL_FAST}
44FLOAT_CONSTRAINTS = {*NUMERIC_CONSTRAINTS, *ALLOW_INF_NAN, *STRICT}
45DECIMAL_CONSTRAINTS = {'max_digits', 'decimal_places', *FLOAT_CONSTRAINTS}
46FRACTION_CONSTRAINTS = {*NUMERIC_CONSTRAINTS, *STRICT}
47INT_CONSTRAINTS = {*NUMERIC_CONSTRAINTS, *STRICT}
48BOOL_CONSTRAINTS = STRICT
49UUID_CONSTRAINTS = STRICT
51DATE_TIME_CONSTRAINTS = {*INEQUALITY, *STRICT}
52TIMEDELTA_CONSTRAINTS = {*NUMERIC_CONSTRAINTS, *STRICT}
53LAX_OR_STRICT_CONSTRAINTS = STRICT
54ENUM_CONSTRAINTS = STRICT
55COMPLEX_CONSTRAINTS = STRICT
57UNION_CONSTRAINTS = {'union_mode'}
58URL_CONSTRAINTS = {
59 'max_length',
60 'allowed_schemes',
61 'host_required',
62 'default_host',
63 'default_port',
64 'default_path',
65 *STRICT,
66}
68CONSTRAINTS_TO_ALLOWED_SCHEMAS: dict[str, set[str]] = defaultdict(set)
70constraint_schema_pairings: list[tuple[set[str], tuple[str, ...]]] = [
71 (STR_CONSTRAINTS, ('str',)),
72 (BYTES_CONSTRAINTS, ('bytes',)),
73 (LIST_CONSTRAINTS, ('list', 'deque')),
74 (TUPLE_CONSTRAINTS, ('tuple',)),
75 (SET_CONSTRAINTS, ('set', 'frozenset')),
76 (DICT_CONSTRAINTS, ('dict', 'frozendict', 'ordered-dict', 'counter')),
77 (GENERATOR_CONSTRAINTS, ('generator',)),
78 (FLOAT_CONSTRAINTS, ('float',)),
79 (INT_CONSTRAINTS, ('int',)),
80 (DATE_TIME_CONSTRAINTS, ('date', 'time', 'datetime')),
81 (TIMEDELTA_CONSTRAINTS, ('timedelta',)),
82 (STRICT, ('typed-dict', 'model')),
83 (UNION_CONSTRAINTS, ('union',)),
84 (URL_CONSTRAINTS, ('url', 'multi-host-url')),
85 (BOOL_CONSTRAINTS, ('bool',)),
86 (UUID_CONSTRAINTS, ('uuid',)),
87 (LAX_OR_STRICT_CONSTRAINTS, ('lax-or-strict',)),
88 (ENUM_CONSTRAINTS, ('enum',)),
89 (DECIMAL_CONSTRAINTS, ('decimal',)),
90 (COMPLEX_CONSTRAINTS, ('complex',)),
91 (FRACTION_CONSTRAINTS, ('fraction',)),
92]
94for constraints, schemas in constraint_schema_pairings:
95 for c in constraints:
96 CONSTRAINTS_TO_ALLOWED_SCHEMAS[c].update(schemas)
99def as_jsonable_value(v: Any) -> Any:
100 if type(v) not in (int, str, float, bytes, bool, type(None)):
101 return to_jsonable_python(v)
102 return v
105def expand_grouped_metadata(annotations: Iterable[Any]) -> Iterable[Any]:
106 """Expand the annotations.
108 Args:
109 annotations: An iterable of annotations.
111 Returns:
112 An iterable of expanded annotations.
114 Example:
115 ```python
116 from annotated_types import Ge, Len
118 from pydantic._internal._known_annotated_metadata import expand_grouped_metadata
120 print(list(expand_grouped_metadata([Ge(4), Len(5)])))
121 #> [Ge(ge=4), MinLen(min_length=5)]
122 ```
123 """
124 import annotated_types as at
126 FieldInfo = import_cached_field_info()
128 for annotation in annotations:
129 if isinstance(annotation, at.GroupedMetadata):
130 yield from annotation
131 elif isinstance(annotation, FieldInfo):
132 yield from annotation.metadata
133 # this is a bit problematic in that it results in duplicate metadata
134 # all of our "consumers" can handle it, but it is not ideal
135 # we probably should split up FieldInfo into:
136 # - annotated types metadata
137 # - individual metadata known only to Pydantic
138 annotation = copy(annotation)
139 annotation.metadata = []
140 yield annotation
141 else:
142 yield annotation
145@lru_cache
146def _get_at_to_constraint_map() -> dict[type, str]:
147 """Return a mapping of annotated types to constraints.
149 Normally, we would define a mapping like this in the module scope, but we can't do that
150 because we don't permit module level imports of `annotated_types`, in an attempt to speed up
151 the import time of `pydantic`. We still only want to have this dictionary defined in one place,
152 so we use this function to cache the result.
153 """
154 import annotated_types as at
156 return {
157 at.Gt: 'gt',
158 at.Ge: 'ge',
159 at.Lt: 'lt',
160 at.Le: 'le',
161 at.MultipleOf: 'multiple_of',
162 at.MinLen: 'min_length',
163 at.MaxLen: 'max_length',
164 }
167def apply_known_metadata(annotation: Any, schema: CoreSchema) -> CoreSchema | None: # noqa: C901
168 """Apply `annotation` to `schema` if it is an annotation we know about (Gt, Le, etc.).
169 Otherwise return `None`.
171 This does not handle all known annotations. If / when it does, it can always
172 return a CoreSchema and return the unmodified schema if the annotation should be ignored.
174 Assumes that GroupedMetadata has already been expanded via `expand_grouped_metadata`.
176 Args:
177 annotation: The annotation.
178 schema: The schema.
180 Returns:
181 An updated schema with annotation if it is an annotation we know about, `None` otherwise.
183 Raises:
184 RuntimeError: If a constraint can't be applied to a specific schema type.
185 ValueError: If an unknown constraint is encountered.
186 """
187 import annotated_types as at
189 from ._validators import NUMERIC_VALIDATOR_LOOKUP, forbid_inf_nan_check
191 schema = schema.copy()
192 schema_update, other_metadata = collect_known_metadata([annotation])
193 schema_type = schema['type']
195 chain_schema_constraints: set[str] = {
196 'pattern',
197 'strip_whitespace',
198 'to_lower',
199 'to_upper',
200 'coerce_numbers_to_str',
201 'ascii_only',
202 }
203 chain_schema_steps: list[CoreSchema] = []
205 for constraint, value in schema_update.items():
206 if constraint not in CONSTRAINTS_TO_ALLOWED_SCHEMAS:
207 raise ValueError(f'Unknown constraint {constraint}')
208 allowed_schemas = CONSTRAINTS_TO_ALLOWED_SCHEMAS[constraint]
210 # if it becomes necessary to handle more than one constraint
211 # in this recursive case with function-after or function-wrap, we should refactor
212 # this is a bit challenging because we sometimes want to apply constraints to the inner schema,
213 # whereas other times we want to wrap the existing schema with a new one that enforces a new constraint.
214 if schema_type in {'function-before', 'function-wrap', 'function-after'} and constraint == 'strict':
215 schema['schema'] = apply_known_metadata(annotation, schema['schema']) # type: ignore # schema is function schema
216 return schema
218 # if we're allowed to apply constraint directly to the schema, like le to int, do that
219 if schema_type in allowed_schemas:
220 if constraint == 'union_mode' and schema_type == 'union':
221 schema['mode'] = value # type: ignore # schema is UnionSchema
222 else:
223 schema[constraint] = value
224 continue
226 # else, apply a function after validator to the schema to enforce the corresponding constraint
227 if constraint in chain_schema_constraints:
229 def _apply_constraint_with_incompatibility_info(
230 value: Any, handler: cs.ValidatorFunctionWrapHandler
231 ) -> Any:
232 try:
233 x = handler(value)
234 except ValidationError as ve:
235 # if the error is about the type, it's likely that the constraint is incompatible the type of the field
236 # for example, the following invalid schema wouldn't be caught during schema build, but rather at this point
237 # with a cryptic 'string_type' error coming from the string validator,
238 # that we'd rather express as a constraint incompatibility error (TypeError)
239 # Annotated[list[int], Field(pattern='abc')]
240 if 'type' in ve.errors()[0]['type']:
241 raise TypeError(
242 f"Unable to apply constraint '{constraint}' to supplied value {value} for schema of type '{schema_type}'" # noqa: B023
243 )
244 raise ve
245 return x
247 chain_schema_steps.append(
248 cs.no_info_wrap_validator_function(
249 _apply_constraint_with_incompatibility_info, cs.str_schema(**{constraint: value})
250 )
251 )
252 elif constraint in NUMERIC_VALIDATOR_LOOKUP:
253 if constraint in LENGTH_CONSTRAINTS:
254 inner_schema = schema
255 while inner_schema['type'] in {'function-before', 'function-wrap', 'function-after'}:
256 inner_schema = inner_schema['schema'] # type: ignore
257 inner_schema_type = inner_schema['type']
258 if inner_schema_type == 'list' or (
259 inner_schema_type == 'json-or-python' and inner_schema['json_schema']['type'] == 'list' # type: ignore
260 ):
261 js_constraint_key = 'minItems' if constraint == 'min_length' else 'maxItems'
262 else:
263 js_constraint_key = 'minLength' if constraint == 'min_length' else 'maxLength'
264 else:
265 js_constraint_key = constraint
267 validator_kwargs = {constraint: value}
268 if constraint == 'decimal_places' and schema_update.get('max_digits') is not None:
269 # The whole digits limit depends on both constraints, and is checked alongside `decimal_places`:
270 validator_kwargs['max_digits'] = schema_update['max_digits']
271 schema = cs.no_info_after_validator_function(
272 partial(NUMERIC_VALIDATOR_LOOKUP[constraint], **validator_kwargs), schema
273 )
274 metadata = schema.get('metadata', {})
275 if (existing_json_schema_updates := metadata.get('pydantic_js_updates')) is not None:
276 metadata['pydantic_js_updates'] = {
277 **existing_json_schema_updates,
278 **{js_constraint_key: as_jsonable_value(value)},
279 }
280 else:
281 metadata['pydantic_js_updates'] = {js_constraint_key: as_jsonable_value(value)}
282 schema['metadata'] = metadata
283 elif constraint == 'allow_inf_nan' and value is False:
284 schema = cs.no_info_after_validator_function(
285 forbid_inf_nan_check,
286 schema,
287 )
288 else:
289 # It's rare that we'd get here, but it's possible if we add a new constraint and forget to handle it
290 # Most constraint errors are caught at runtime during attempted application
291 raise RuntimeError(f"Unable to apply constraint '{constraint}' to schema of type '{schema_type}'")
293 for annotation in other_metadata:
294 if (annotation_type := type(annotation)) in (at_to_constraint_map := _get_at_to_constraint_map()):
295 constraint = at_to_constraint_map[annotation_type]
296 validator = NUMERIC_VALIDATOR_LOOKUP.get(constraint)
297 if validator is None:
298 raise ValueError(f'Unknown constraint {constraint}')
299 schema = cs.no_info_after_validator_function(
300 partial(validator, {constraint: getattr(annotation, constraint)}), schema
301 )
302 continue
303 elif isinstance(annotation, (at.Predicate, at.Not)):
304 predicate_name = f'{annotation.func.__qualname__!r} ' if hasattr(annotation.func, '__qualname__') else ''
306 # Note: B023 is ignored because even though we iterate over `other_metadata`, it is guaranteed
307 # to be of length 1. `apply_known_metadata()` is called from `GenerateSchema`, where annotations
308 # were already expanded via `expand_grouped_metadata()`. Confusing, but this falls into the annotations
309 # refactor.
310 if isinstance(annotation, at.Predicate):
312 def val_func(v: Any) -> Any:
313 predicate_satisfied = annotation.func(v) # noqa: B023
314 if not predicate_satisfied:
315 raise PydanticCustomError(
316 'predicate_failed',
317 f'Predicate {predicate_name}failed', # pyright: ignore[reportArgumentType] # noqa: B023
318 )
319 return v
321 else:
323 def val_func(v: Any) -> Any:
324 predicate_satisfied = annotation.func(v) # noqa: B023
325 if predicate_satisfied:
326 raise PydanticCustomError(
327 'not_operation_failed',
328 f'Not of {predicate_name}failed', # pyright: ignore[reportArgumentType] # noqa: B023
329 )
330 return v
332 schema = cs.no_info_after_validator_function(val_func, schema)
333 else:
334 # ignore any other unknown metadata
335 return None
337 if chain_schema_steps:
338 chain_schema_steps = [schema] + chain_schema_steps
339 return cs.chain_schema(chain_schema_steps)
341 return schema
344def collect_known_metadata(annotations: Iterable[Any]) -> tuple[dict[str, Any], list[Any]]:
345 """Split `annotations` into known metadata and unknown annotations.
347 Args:
348 annotations: An iterable of annotations.
350 Returns:
351 A tuple contains a dict of known metadata and a list of unknown annotations.
353 Example:
354 ```python
355 from annotated_types import Gt, Len
357 from pydantic._internal._known_annotated_metadata import collect_known_metadata
359 print(collect_known_metadata([Gt(1), Len(42), ...]))
360 #> ({'gt': 1, 'min_length': 42}, [Ellipsis])
361 ```
362 """
363 annotations = expand_grouped_metadata(annotations)
365 res: dict[str, Any] = {}
366 remaining: list[Any] = []
368 for annotation in annotations:
369 # isinstance(annotation, PydanticMetadata) also covers ._fields:_PydanticGeneralMetadata
370 if isinstance(annotation, PydanticMetadata):
371 res.update(annotation.__dict__)
372 # we don't use dataclasses.asdict because that recursively calls asdict on the field values
373 elif (annotation_type := type(annotation)) in (at_to_constraint_map := _get_at_to_constraint_map()):
374 constraint = at_to_constraint_map[annotation_type]
375 res[constraint] = getattr(annotation, constraint)
376 elif isinstance(annotation, type) and issubclass(annotation, PydanticMetadata):
377 # also support PydanticMetadata classes being used without initialisation,
378 # e.g. `Annotated[int, Strict]` as well as `Annotated[int, Strict()]`
379 res.update({k: v for k, v in vars(annotation).items() if not k.startswith('_')})
380 else:
381 remaining.append(annotation)
382 # Nones can sneak in but pydantic-core will reject them
383 # it'd be nice to clean things up so we don't put in None (we probably don't _need_ to, it was just easier)
384 # but this is simple enough to kick that can down the road
385 res = {k: v for k, v in res.items() if v is not None}
386 return res, remaining
389def check_metadata(metadata: dict[str, Any], allowed: Iterable[str], source_type: Any) -> None:
390 """A small utility function to validate that the given metadata can be applied to the target.
391 More than saving lines of code, this gives us a consistent error message for all of our internal implementations.
393 Args:
394 metadata: A dict of metadata.
395 allowed: An iterable of allowed metadata.
396 source_type: The source type.
398 Raises:
399 TypeError: If there is metadatas that can't be applied on source type.
400 """
401 unknown = metadata.keys() - set(allowed)
402 if unknown:
403 raise TypeError(
404 f'The following constraints cannot be applied to {source_type!r}: {", ".join([f"{k!r}" for k in unknown])}'
405 )